Evidence map›Paper›PMID 40806603›Full record

ArticleInternational journal of molecular sciences2025

Multitarget Design of Steroidal Inhibitors Against Hormone-Dependent Breast Cancer: An Integrated In Silico Approach.

Juan Rodríguez-Macías, Oscar Saurith-Coronell, Carlos Vargas-Echeverria, Daniel Insuasty Delgado, Edgar A Márquez Brazón, Ricardo Gutiérrez De Aguas, José R Mora, José L Paz, Yovanni Marrero-Ponce

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in International journal of molecular sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Juan Rodríguez-MacíasFacultad de Ciencias de la Salud, Exactas y Naturales, Universidad Libre, Barranquilla 080001, Colombia.ORCID 0000-0001-5247-867X
Oscar Saurith-CoronellGrupo de Investigaciones en Química y Biología, Departamento de Química y Biología, Facultad de Ciencias Básicas, Universidad del Norte, Carrera 51B, Km 5, Vía Puerto Colombia, Barranquilla 081007, Colombia.ORCID 0009-0008-4454-3126
Carlos Vargas-EcheverriaGrupo de Investigaciones en Química y Biología, Departamento de Química y Biología, Facultad de Ciencias Básicas, Universidad del Norte, Carrera 51B, Km 5, Vía Puerto Colombia, Barranquilla 081007, Colombia.ORCID 0009-0000-8160-3572
Daniel Insuasty DelgadoGrupo de Investigaciones en Química y Biología, Departamento de Química y Biología, Facultad de Ciencias Básicas, Universidad del Norte, Carrera 51B, Km 5, Vía Puerto Colombia, Barranquilla 081007, Colombia.ORCID 0000-0001-9662-9505
Edgar A Márquez BrazónGrupo de Investigaciones en Química y Biología, Departamento de Química y Biología, Facultad de Ciencias Básicas, Universidad del Norte, Carrera 51B, Km 5, Vía Puerto Colombia, Barranquilla 081007, Colombia.ORCID 0000-0002-7503-1528
Ricardo Gutiérrez De AguasGrupo de Investigaciones en Química y Biología, Departamento de Química y Biología, Facultad de Ciencias Básicas, Universidad del Norte, Carrera 51B, Km 5, Vía Puerto Colombia, Barranquilla 081007, Colombia.
José R MoraGrupo de Química Computacional y Teórica (QCT-USFQ), Departamento de Ingeniería Química, Universidad San Francisco de Quito, Diego de Robles y Vía Interoceánica, Quito 170901, Ecuador.ORCID 0000-0001-6128-9504
José L PazDepartamento Académico de Química Inorgánica, Facultad de Química e Ingeniería Química, Universidad Nacional Mayor de San Marcos, Lima 15081, Peru.ORCID 0000-0002-6177-7919
Yovanni Marrero-PonceFacultad de Ingeniería, Universidad Panamericana, Augusto Rodin No. 498, Insurgentes Mixcoac, Benito Juárez, Ciudad de México 03920, Mexico.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hormone-dependent breast cancer, particularly in its treatment-resistant forms, remains a significant therapeutic challenge. In this study, we applied a fully computational strategy to design steroid-based compounds capable of simultaneously targeting three key receptors involved in disease progression: progesterone receptor (PR), estrogen receptor alpha (ER-α), and HER2. Using a robust 3D-QSAR model (R

Indexed as

Antineoplastic AgentsBreast NeoplasmsDrug DesignNeoplasms, Hormone-DependentSteroidsComputer SimulationErb-b2 Receptor Tyrosine KinasesEstrogen Receptor alphaFemaleHumansHydrogen BondingMolecular Docking SimulationMolecular Dynamics SimulationQuantitative Structure-Activity RelationshipReceptors, ProgesteroneAntineoplastic AgentsERBB2 protein, humanErb-b2 Receptor Tyrosine KinasesESR1 protein, humanEstrogen Receptor alphaReceptors, ProgesteroneSteroidsdockingERαHER2inhibitorsPRQSARsteroids

Identifiers

PMID40806603
PMCPMC12348013

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.